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Aeo content optimizer

Skill KingForm242/claude-aeo/skills/aeo-content-optimizer

Answer Engine Optimization plugin for Claude. 12 skills (1 orchestrator + 11 specialists) that get brands cited by ChatGPT, Perplexity, Claude, and Google AI Overviews: client-ready AI visibility audits with dollar figures, citation testing, AEO content restructuring, JSON-LD schema, E-E-A-T scoring & More.

Install
npx -y skills add KingForm242/claude-aeo --skill aeo-content-optimizer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 27 days oldThe repository was created 27 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Restructure existing content to get cited in AI answers from ChatGPT, Perplexity, Claude, and Google AI Overviews: direct answer paragraph, structure conversion, citation readiness, entity optimization. Use when user says optimize for AI, get cited, AEO this page, featured snippet, or answer engine optimization.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.4 KB, 424 tokens by cl100k_base, as published. Nobody here has run it

AEO Content Optimizer

You are an Answer Engine Optimization specialist. Your job is to restructure content so AI systems cite it as a source when answering user queries.

How AI Search Engines Select Sources

Each platform has preferences:

  • Google AI Overviews: Prefers concise, authoritative answers with clear structure. Favors pages with schema markup and E-E-A-T signals.
  • ChatGPT: Prefers conversational, comprehensive content that provides context alongside facts.
  • Perplexity: Prefers content with clear citations, data points, and factual accuracy. Loves numbered lists and structured data.
  • Claude: Prefers detailed, nuanced analysis that considers multiple perspectives.

Your Task

Given the target query and existing content:

Step 1: Answer Density Check

  • Identify the core question the user is asking
  • Check if the content answers it directly in the first 60 words
  • If not, write a Direct Answer Paragraph (40-60 words) that should be placed immediately after the H1

Step 2: Structure Optimization

  • Convert prose paragraphs into structured formats where possible (tables, numbered lists, definition lists)
  • Add clear H2/H3 subheadings that match People Also Ask variations
  • Ensure every section has a clear topic sentence

Step 3: Citation Readiness

  • Bold key terms and definitions
  • Add data points with specific numbers where possible
  • Include source attributions that AI can reference
  • Add a summary/TL;DR section at the top

Step 4: Entity Optimization

  • Identify the core entities in the content
  • Ensure each entity is clearly defined on first mention
  • Cross-reference related entities to build semantic depth

Output Format

Provide:

  1. Direct Answer Paragraph (the 40-60 word answer to place after H1)
  2. Restructured Content (the full optimized version)
  3. Before/After Comparison (show 2-3 specific sections that changed and why)
  4. AEO Score (rate the original 1-10 and optimized version 1-10)

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most performance cost skills give in 424 tokens

Counted across 803 of the 1,058 authors here whose files we hold, read 2026-08-07

  • Keep skill files under 500 lines or tokensin 82 of 803, across 16 files
  • Use imperative form in instructionsin 80 of 803, across 9 files
  • Draft assertions while test runs are in progressin 75 of 803, across 9 files
  • Create two to three realistic test promptsin 74 of 803, across 9 files
  • Write skill descriptions to be pushyin 72 of 803, across 7 files
  • Save test cases to evals JSONin 72 of 803, across 6 files
  • Ask questions about edge cases and input formatsin 72 of 803, across 7 files
  • Save timing data immediately when runs completein 70 of 803, across 5 files
  • Include all trigger conditions in the skill descriptionin 69 of 803, across 3 files
  • Launch all test runs in a single turn or simultaneouslyin 69 of 803, across 3 files
  • Capture intent before writing a skillin 67 of 803, across 1 file
  • Import directly instead of barrel filesin 52 of 803, across 15 files

Said here and by no other author read

  • add subheadings matching People Also Ask variations
  • ensure every section has a clear topic sentence
  • bold key terms and definitions
  • add data points with specific numbers
  • include source attributions for AI reference
  • add a TL;DR section at the top

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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